Tensor Decomposition for Dimension Reduction

Abstract

Tensor data are data with multiway array structure. They are often very high dimensional and are routinely encountered in many scientific fields. Dimension reduction is the technique of reducing the number of underlying variables for compressed data representation and for model parsimony. Tensor dimension reduction aims for reducing the tensor data dimension while keeping data`s tensor structure.